@inproceedings{berka-etal-2012-automatic,
title = "Automatic {MT} Error Analysis: Hjerson Helping Addicter",
author = "Berka, Jan and
Bojar, Ond{\v{r}}ej and
Fishel, Mark and
Popovi{\'c}, Maja and
Zeman, Daniel",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Do{\u{g}}an, Mehmet U{\u{g}}ur and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
month = may,
year = "2012",
address = "Istanbul, Turkey",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/336_Paper.pdf",
pages = "2158--2163",
abstract = "We present a complex, open source tool for detailed machine translation error analysis providing the user with automatic error detection and classification, several monolingual alignment algorithms as well as with training and test corpus browsing. The tool is the result of a merge of automatic error detection and classification of Hjerson (Popovi{\'c}, 2011) and Addicter (Zeman et al., 2011) into the pipeline and web visualization of Addicter. It classifies errors into categories similar to those of Vilar et al. (2006), such as: morphological, reordering, missing words, extra words and lexical errors. The graphical user interface shows alignments in both training corpus and test data; the different classes of errors are colored. Also, the summary of errors can be displayed to provide an overall view of the MT system's weaknesses. The tool was developed in Linux, but it was tested on Windows too.",
}
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%0 Conference Proceedings
%T Automatic MT Error Analysis: Hjerson Helping Addicter
%A Berka, Jan
%A Bojar, Ondřej
%A Fishel, Mark
%A Popović, Maja
%A Zeman, Daniel
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Doğan, Mehmet Uğur
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 May
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F berka-etal-2012-automatic
%X We present a complex, open source tool for detailed machine translation error analysis providing the user with automatic error detection and classification, several monolingual alignment algorithms as well as with training and test corpus browsing. The tool is the result of a merge of automatic error detection and classification of Hjerson (Popović, 2011) and Addicter (Zeman et al., 2011) into the pipeline and web visualization of Addicter. It classifies errors into categories similar to those of Vilar et al. (2006), such as: morphological, reordering, missing words, extra words and lexical errors. The graphical user interface shows alignments in both training corpus and test data; the different classes of errors are colored. Also, the summary of errors can be displayed to provide an overall view of the MT system’s weaknesses. The tool was developed in Linux, but it was tested on Windows too.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/336_Paper.pdf
%P 2158-2163
Markdown (Informal)
[Automatic MT Error Analysis: Hjerson Helping Addicter](http://www.lrec-conf.org/proceedings/lrec2012/pdf/336_Paper.pdf) (Berka et al., LREC 2012)
ACL
- Jan Berka, Ondřej Bojar, Mark Fishel, Maja Popović, and Daniel Zeman. 2012. Automatic MT Error Analysis: Hjerson Helping Addicter. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 2158–2163, Istanbul, Turkey. European Language Resources Association (ELRA).